In
statistics and in
machine learning, a
linear predictor function is a
linear function (
linear combination) of a set of coefficients and explanatory variables (
independent variables), whose value is used to predict the outcome of a
dependent variable. Functions of this sort are standard in
linear regression, where the coefficients are termed
regression coefficients. However, they also occur in various types of
linear classifiers (e.g.
logistic regression,
perceptrons,
support vector machines, and
linear discriminant analysis), as well as in various other models, such as
principal component analysis and
factor analysis. In many of these models, the coefficients are referred to as "weights".